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22 Commits

Author SHA1 Message Date
UncleCode
ac9d83c72f Update gitignore 2024-10-27 19:29:04 +08:00
UncleCode
ff9149b5c9 Merge branch 'main' of https://github.com/unclecode/crawl4ai 2024-10-27 19:28:05 +08:00
UncleCode
32f57c49d6 Merge pull request #194 from IdrisHanafi/feat/customize-crawl-base-directory
Support for custom crawl base directory
2024-10-24 13:09:27 +02:00
Idris Hanafi
a5f627ba1a feat: customize crawl base directory 2024-10-21 17:58:39 -04:00
UncleCode
dbb587d681 Update gitignore 2024-10-17 21:38:48 +08:00
unclecode
9ffa34b697 Update README 2024-10-14 22:58:27 +08:00
unclecode
740802c491 Merge branch '0.3.6' 2024-10-14 22:55:24 +08:00
unclecode
b9ac96c332 Merge branch 'main' of https://github.com/unclecode/crawl4ai 2024-10-14 22:54:23 +08:00
unclecode
d06535388a Update gitignore 2024-10-14 22:53:56 +08:00
unclecode
2b73bdf6b0 Update changelog 2024-10-14 21:04:02 +08:00
unclecode
6aa803d712 Update gitignore 2024-10-14 21:03:40 +08:00
unclecode
320afdea64 feat: Enhance crawler flexibility and LLM extraction capabilities
- Add browser type selection (Chromium, Firefox, WebKit)
- Implement iframe content extraction
- Improve image processing and dimension updates
- Add custom headers support in AsyncPlaywrightCrawlerStrategy
- Enhance delayed content retrieval with new parameter
- Optimize HTML sanitization and Markdown conversion
- Update examples in quickstart_async.py for new features
2024-10-14 21:03:28 +08:00
UncleCode
ccbe72cfc1 Merge pull request #135 from hitesh22rana/fix/docs-example
docs: fixed css_selector for example
2024-10-13 14:39:07 +08:00
unclecode
b9bbd42373 Update Quickstart examples 2024-10-13 14:37:45 +08:00
unclecode
68e9144ce3 feat: Enhance crawling control and LLM extraction flexibility
- Add before_retrieve_html hook and delay_before_return_html option
- Implement flexible page_timeout for smart_wait function
- Support extra_args and custom headers in LLM extraction
- Allow arbitrary kwargs in AsyncWebCrawler initialization
- Improve perform_completion_with_backoff for custom API calls
- Update examples with new features and diverse LLM providers
2024-10-12 14:48:22 +08:00
unclecode
9b2b267820 CHANGELOG UPDATE 2024-10-12 13:42:56 +08:00
unclecode
ff3524d9b1 feat(v0.3.6): Add screenshot capture, delayed content, and custom timeouts
- Implement screenshot capture functionality
- Add delayed content retrieval method
- Introduce custom page timeout parameter
- Enhance LLM support with multiple providers
- Improve database schema auto-updates
- Optimize image processing in WebScrappingStrategy
- Update error handling and logging
- Expand examples in quickstart_async.py
2024-10-12 13:42:42 +08:00
unclecode
b99d20b725 Add pypi_build.sh to .gitignore 2024-10-08 18:10:57 +08:00
hitesh22rana
768b93140f docs: fixed css_selector for example 2024-10-05 00:25:41 +09:00
unclecode
4750810a67 Enhance AsyncWebCrawler with smart waiting and screenshot capabilities
- Implement smart_wait function in AsyncPlaywrightCrawlerStrategy
- Add screenshot support to AsyncCrawlResponse and AsyncWebCrawler
- Improve error handling and timeout management in crawling process
- Fix typo in CrawlResult model (responser_headers -> response_headers)
- Update .gitignore to exclude additional files
- Adjust import path in test_basic_crawling.py
2024-10-02 17:34:56 +08:00
unclecode
e0e0db4247 Bump version to 0.3.4 2024-09-29 17:07:52 +08:00
unclecode
bccadec887 Remove dependency on psutil, PyYaml, and extend requests version range 2024-09-29 17:07:06 +08:00
20 changed files with 831 additions and 171 deletions

11
.gitignore vendored
View File

@@ -197,3 +197,14 @@ tmp/
test_env/
**/.DS_Store
**/.DS_Store
todo.md
git_changes.py
git_changes.md
pypi_build.sh
git_issues.py
git_issues.md
.tests/
.issues/

View File

@@ -1,5 +1,92 @@
# Changelog
## [v0.3.6] - 2024-10-12
### 1. Improved Crawling Control
- **New Hook**: Added `before_retrieve_html` hook in `AsyncPlaywrightCrawlerStrategy`.
- **Delayed HTML Retrieval**: Introduced `delay_before_return_html` parameter to allow waiting before retrieving HTML content.
- Useful for pages with delayed content loading.
- **Flexible Timeout**: `smart_wait` function now uses `page_timeout` (default 60 seconds) instead of a fixed 30-second timeout.
- Provides better handling for slow-loading pages.
- **How to use**: Set `page_timeout=your_desired_timeout` (in milliseconds) when calling `crawler.arun()`.
### 2. Browser Type Selection
- Added support for different browser types (Chromium, Firefox, WebKit).
- Users can now specify the browser type when initializing AsyncWebCrawler.
- **How to use**: Set `browser_type="firefox"` or `browser_type="webkit"` when initializing AsyncWebCrawler.
### 3. Screenshot Capture
- Added ability to capture screenshots during crawling.
- Useful for debugging and content verification.
- **How to use**: Set `screenshot=True` when calling `crawler.arun()`.
### 4. Enhanced LLM Extraction Strategy
- Added support for multiple LLM providers (OpenAI, Hugging Face, Ollama).
- **Custom Arguments**: Added support for passing extra arguments to LLM providers via `extra_args` parameter.
- **Custom Headers**: Users can now pass custom headers to the extraction strategy.
- **How to use**: Specify the desired provider and custom arguments when using `LLMExtractionStrategy`.
### 5. iframe Content Extraction
- New feature to process and extract content from iframes.
- **How to use**: Set `process_iframes=True` in the crawl method.
### 6. Delayed Content Retrieval
- Introduced `get_delayed_content` method in `AsyncCrawlResponse`.
- Allows retrieval of content after a specified delay, useful for dynamically loaded content.
- **How to use**: Access `result.get_delayed_content(delay_in_seconds)` after crawling.
## Improvements and Optimizations
### 1. AsyncWebCrawler Enhancements
- **Flexible Initialization**: Now accepts arbitrary keyword arguments, passed directly to the crawler strategy.
- Allows for more customized setups.
### 2. Image Processing Optimization
- Enhanced image handling in WebScrappingStrategy.
- Added filtering for small, invisible, or irrelevant images.
- Improved image scoring system for better content relevance.
- Implemented JavaScript-based image dimension updating for more accurate representation.
### 3. Database Schema Auto-updates
- Automatic database schema updates ensure compatibility with the latest version.
### 4. Enhanced Error Handling and Logging
- Improved error messages and logging for easier debugging.
### 5. Content Extraction Refinements
- Refined HTML sanitization process.
- Improved handling of base64 encoded images.
- Enhanced Markdown conversion process.
- Optimized content extraction algorithms.
### 6. Utility Function Enhancements
- `perform_completion_with_backoff` function now supports additional arguments for more customized API calls to LLM providers.
## Bug Fixes
- Fixed an issue where image tags were being prematurely removed during content extraction.
## Examples and Documentation
- Updated `quickstart_async.py` with examples of:
- Using custom headers in LLM extraction.
- Different LLM provider usage (OpenAI, Hugging Face, Ollama).
- Custom browser type usage.
## Developer Notes
- Refactored code for better maintainability, flexibility, and performance.
- Enhanced type hinting throughout the codebase for improved development experience.
- Expanded error handling for more robust operation.
These updates significantly enhance the flexibility, accuracy, and robustness of crawl4ai, providing users with more control and options for their web crawling and content extraction tasks.
## [v0.3.5] - 2024-09-02
Enhance AsyncWebCrawler with smart waiting and screenshot capabilities
- Implement smart_wait function in AsyncPlaywrightCrawlerStrategy
- Add screenshot support to AsyncCrawlResponse and AsyncWebCrawler
- Improve error handling and timeout management in crawling process
- Fix typo in CrawlResult model (responser_headers -> response_headers)
## [v0.2.77] - 2024-08-04
Significant improvements in text processing and performance:

View File

@@ -10,6 +10,14 @@ Crawl4AI simplifies asynchronous web crawling and data extraction, making it acc
> Looking for the synchronous version? Check out [README.sync.md](./README.sync.md). You can also access the previous version in the branch [V0.2.76](https://github.com/unclecode/crawl4ai/blob/v0.2.76).
## New update 0.3.6
- 🌐 Multi-browser support (Chromium, Firefox, WebKit)
- 🖼️ Improved image processing with lazy-loading detection
- 🔧 Custom page timeout parameter for better control over crawling behavior
- 🕰️ Enhanced handling of delayed content loading
- 🔑 Custom headers support for LLM interactions
- 🖼️ iframe content extraction for comprehensive page analysis
- ⏱️ Flexible timeout and delayed content retrieval options
## Try it Now!
@@ -39,7 +47,6 @@ Crawl4AI simplifies asynchronous web crawling and data extraction, making it acc
- 🔄 Session management for complex multi-page crawling scenarios
- 🌐 Asynchronous architecture for improved performance and scalability
## Installation 🛠️
Crawl4AI offers flexible installation options to suit various use cases. You can install it as a Python package or use Docker.
@@ -56,9 +63,21 @@ For basic web crawling and scraping tasks:
pip install crawl4ai
```
By default this will install the asynchronous version of Crawl4AI, using Playwright for web crawling.
By default, this will install the asynchronous version of Crawl4AI, using Playwright for web crawling.
👉 Note: The standard version of Crawl4AI uses Playwright for asynchronous crawling. If you encounter an error saying that Playwright is not installed, you can run playwright install. However, this should be done automatically during the setup process.
👉 Note: When you install Crawl4AI, the setup script should automatically install and set up Playwright. However, if you encounter any Playwright-related errors, you can manually install it using one of these methods:
1. Through the command line:
```bash
playwright install
```
2. If the above doesn't work, try this more specific command:
```bash
python -m playwright install chromium
```
This second method has proven to be more reliable in some cases.
#### Installation with Synchronous Version
@@ -113,7 +132,7 @@ async def main():
result = await crawler.arun(
url="https://www.nbcnews.com/business",
js_code=js_code,
css_selector="article.tease-card",
css_selector=".wide-tease-item__description",
bypass_cache=True
)
print(result.extracted_content)

View File

@@ -3,7 +3,7 @@
from .async_webcrawler import AsyncWebCrawler
from .models import CrawlResult
__version__ = "0.3.3"
__version__ = "0.3.6"
__all__ = [
"AsyncWebCrawler",

View File

@@ -1,30 +1,27 @@
import asyncio
import base64, time
from abc import ABC, abstractmethod
from typing import Callable, Dict, Any, List, Optional
from typing import Callable, Dict, Any, List, Optional, Awaitable
import os
import psutil
from playwright.async_api import async_playwright, Page, Browser, Error
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont
from .utils import sanitize_input_encode
from .utils import sanitize_input_encode, calculate_semaphore_count
import json, uuid
import hashlib
from pathlib import Path
from playwright.async_api import ProxySettings
from pydantic import BaseModel
def calculate_semaphore_count():
cpu_count = os.cpu_count()
memory_gb = psutil.virtual_memory().total / (1024 ** 3) # Convert to GB
base_count = max(1, cpu_count // 2)
memory_based_cap = int(memory_gb / 2) # Assume 2GB per instance
return min(base_count, memory_based_cap)
class AsyncCrawlResponse(BaseModel):
html: str
response_headers: Dict[str, str]
status_code: int
screenshot: Optional[str] = None
get_delayed_content: Optional[Callable[[Optional[float]], Awaitable[str]]] = None
class Config:
arbitrary_types_allowed = True
class AsyncCrawlerStrategy(ABC):
@abstractmethod
@@ -53,7 +50,8 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
self.user_agent = kwargs.get("user_agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36")
self.proxy = kwargs.get("proxy")
self.headless = kwargs.get("headless", True)
self.headers = {}
self.browser_type = kwargs.get("browser_type", "chromium") # New parameter
self.headers = kwargs.get("headers", {})
self.sessions = {}
self.session_ttl = 1800
self.js_code = js_code
@@ -66,7 +64,8 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
'on_execution_started': None,
'before_goto': None,
'after_goto': None,
'before_return_html': None
'before_return_html': None,
'before_retrieve_html': None
}
async def __aenter__(self):
@@ -82,7 +81,6 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
if self.browser is None:
browser_args = {
"headless": self.headless,
# "headless": False,
"args": [
"--disable-gpu",
"--disable-dev-shm-usage",
@@ -97,7 +95,14 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
browser_args["proxy"] = proxy_settings
# Select the appropriate browser based on the browser_type
if self.browser_type == "firefox":
self.browser = await self.playwright.firefox.launch(**browser_args)
elif self.browser_type == "webkit":
self.browser = await self.playwright.webkit.launch(**browser_args)
else:
self.browser = await self.playwright.chromium.launch(**browser_args)
await self.execute_hook('on_browser_created', self.browser)
async def close(self):
@@ -147,6 +152,44 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
for sid in expired_sessions:
asyncio.create_task(self.kill_session(sid))
async def smart_wait(self, page: Page, wait_for: str, timeout: float = 30000):
wait_for = wait_for.strip()
if wait_for.startswith('js:'):
# Explicitly specified JavaScript
js_code = wait_for[3:].strip()
return await self.csp_compliant_wait(page, js_code, timeout)
elif wait_for.startswith('css:'):
# Explicitly specified CSS selector
css_selector = wait_for[4:].strip()
try:
await page.wait_for_selector(css_selector, timeout=timeout)
except Error as e:
if 'Timeout' in str(e):
raise TimeoutError(f"Timeout after {timeout}ms waiting for selector '{css_selector}'")
else:
raise ValueError(f"Invalid CSS selector: '{css_selector}'")
else:
# Auto-detect based on content
if wait_for.startswith('()') or wait_for.startswith('function'):
# It's likely a JavaScript function
return await self.csp_compliant_wait(page, wait_for, timeout)
else:
# Assume it's a CSS selector first
try:
await page.wait_for_selector(wait_for, timeout=timeout)
except Error as e:
if 'Timeout' in str(e):
raise TimeoutError(f"Timeout after {timeout}ms waiting for selector '{wait_for}'")
else:
# If it's not a timeout error, it might be an invalid selector
# Let's try to evaluate it as a JavaScript function as a fallback
try:
return await self.csp_compliant_wait(page, f"() => {{{wait_for}}}", timeout)
except Error:
raise ValueError(f"Invalid wait_for parameter: '{wait_for}'. "
"It should be either a valid CSS selector, a JavaScript function, "
"or explicitly prefixed with 'js:' or 'css:'.")
async def csp_compliant_wait(self, page: Page, user_wait_function: str, timeout: float = 30000):
wrapper_js = f"""
@@ -172,6 +215,48 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
except Exception as e:
raise RuntimeError(f"Error in wait condition: {str(e)}")
async def process_iframes(self, page):
# Find all iframes
iframes = await page.query_selector_all('iframe')
for i, iframe in enumerate(iframes):
try:
# Add a unique identifier to the iframe
await iframe.evaluate(f'(element) => element.id = "iframe-{i}"')
# Get the frame associated with this iframe
frame = await iframe.content_frame()
if frame:
# Wait for the frame to load
await frame.wait_for_load_state('load', timeout=30000) # 30 seconds timeout
# Extract the content of the iframe's body
iframe_content = await frame.evaluate('() => document.body.innerHTML')
# Generate a unique class name for this iframe
class_name = f'extracted-iframe-content-{i}'
# Replace the iframe with a div containing the extracted content
_iframe = iframe_content.replace('`', '\\`')
await page.evaluate(f"""
() => {{
const iframe = document.getElementById('iframe-{i}');
const div = document.createElement('div');
div.innerHTML = `{_iframe}`;
div.className = '{class_name}';
iframe.replaceWith(div);
}}
""")
else:
print(f"Warning: Could not access content frame for iframe {i}")
except Exception as e:
print(f"Error processing iframe {i}: {str(e)}")
# Return the page object
return page
async def crawl(self, url: str, **kwargs) -> AsyncCrawlResponse:
response_headers = {}
status_code = None
@@ -216,7 +301,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
if not kwargs.get("js_only", False):
await self.execute_hook('before_goto', page)
response = await page.goto(url, wait_until="domcontentloaded", timeout=60000)
response = await page.goto(url, wait_until="domcontentloaded", timeout=kwargs.get("page_timeout", 60000))
await self.execute_hook('after_goto', page)
# Get status code and headers
@@ -226,6 +311,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
status_code = 200
response_headers = {}
await page.wait_for_selector('body')
await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
@@ -259,22 +345,89 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
wait_for = kwargs.get("wait_for")
if wait_for:
try:
await self.csp_compliant_wait(page, wait_for, timeout=kwargs.get("timeout", 30000))
await self.smart_wait(page, wait_for, timeout=kwargs.get("page_timeout", 60000))
except Exception as e:
raise RuntimeError(f"Custom wait condition failed: {str(e)}")
# try:
# await page.wait_for_function(wait_for)
# # if callable(wait_for):
# # await page.wait_for_function(wait_for)
# # elif isinstance(wait_for, str):
# # await page.wait_for_selector(wait_for)
# # else:
# # raise ValueError("wait_for must be either a callable or a CSS selector string")
# except Error as e:
# raise Error(f"Custom wait condition failed: {str(e)}")
raise RuntimeError(f"Wait condition failed: {str(e)}")
# Check if kwargs has screenshot=True then take screenshot
screenshot_data = None
if kwargs.get("screenshot"):
screenshot_data = await self.take_screenshot(url)
# New code to update image dimensions
update_image_dimensions_js = """
() => {
return new Promise((resolve) => {
const filterImage = (img) => {
// Filter out images that are too small
if (img.width < 100 && img.height < 100) return false;
// Filter out images that are not visible
const rect = img.getBoundingClientRect();
if (rect.width === 0 || rect.height === 0) return false;
// Filter out images with certain class names (e.g., icons, thumbnails)
if (img.classList.contains('icon') || img.classList.contains('thumbnail')) return false;
// Filter out images with certain patterns in their src (e.g., placeholder images)
if (img.src.includes('placeholder') || img.src.includes('icon')) return false;
return true;
};
const images = Array.from(document.querySelectorAll('img')).filter(filterImage);
let imagesLeft = images.length;
if (imagesLeft === 0) {
resolve();
return;
}
const checkImage = (img) => {
if (img.complete && img.naturalWidth !== 0) {
img.setAttribute('width', img.naturalWidth);
img.setAttribute('height', img.naturalHeight);
imagesLeft--;
if (imagesLeft === 0) resolve();
}
};
images.forEach(img => {
checkImage(img);
if (!img.complete) {
img.onload = () => {
checkImage(img);
};
img.onerror = () => {
imagesLeft--;
if (imagesLeft === 0) resolve();
};
}
});
// Fallback timeout of 5 seconds
setTimeout(() => resolve(), 5000);
});
}
"""
await page.evaluate(update_image_dimensions_js)
# Wait a bit for any onload events to complete
await page.wait_for_timeout(100)
# Process iframes
if kwargs.get("process_iframes", False):
page = await self.process_iframes(page)
await self.execute_hook('before_retrieve_html', page)
# Check if delay_before_return_html is set then wait for that time
delay_before_return_html = kwargs.get("delay_before_return_html")
if delay_before_return_html:
await asyncio.sleep(delay_before_return_html)
html = await page.content()
page = await self.execute_hook('before_return_html', page, html)
await self.execute_hook('before_return_html', page, html)
if self.verbose:
print(f"[LOG] ✅ Crawled {url} successfully!")
@@ -290,7 +443,20 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
"status_code": status_code
}, f)
response = AsyncCrawlResponse(html=html, response_headers=response_headers, status_code=status_code)
async def get_delayed_content(delay: float = 5.0) -> str:
if self.verbose:
print(f"[LOG] Waiting for {delay} seconds before retrieving content for {url}")
await asyncio.sleep(delay)
return await page.content()
response = AsyncCrawlResponse(
html=html,
response_headers=response_headers,
status_code=status_code,
screenshot=screenshot_data,
get_delayed_content=get_delayed_content
)
return response
except Error as e:
raise Error(f"Failed to crawl {url}: {str(e)}")
@@ -348,7 +514,6 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
except Error as e:
raise Error(f"Failed to execute JavaScript or wait for condition in session {session_id}: {str(e)}")
async def crawl_many(self, urls: List[str], **kwargs) -> List[AsyncCrawlResponse]:
semaphore_count = kwargs.get('semaphore_count', calculate_semaphore_count())
semaphore = asyncio.Semaphore(semaphore_count)
@@ -361,11 +526,13 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
results = await asyncio.gather(*tasks, return_exceptions=True)
return [result if not isinstance(result, Exception) else str(result) for result in results]
async def take_screenshot(self, url: str) -> str:
async def take_screenshot(self, url: str, wait_time = 1000) -> str:
async with await self.browser.new_context(user_agent=self.user_agent) as context:
page = await context.new_page()
try:
await page.goto(url, wait_until="domcontentloaded")
await page.goto(url, wait_until="domcontentloaded", timeout=30000)
# Wait for a specified time (default is 1 second)
await page.wait_for_timeout(wait_time)
screenshot = await page.screenshot(full_page=True)
return base64.b64encode(screenshot).decode('utf-8')
except Exception as e:

View File

@@ -29,14 +29,31 @@ class AsyncDatabaseManager:
)
''')
await db.commit()
await self.update_db_schema()
async def aalter_db_add_screenshot(self, new_column: str = "media"):
async def update_db_schema(self):
async with aiosqlite.connect(self.db_path) as db:
# Check if the 'media' column exists
cursor = await db.execute("PRAGMA table_info(crawled_data)")
columns = await cursor.fetchall()
column_names = [column[1] for column in columns]
if 'media' not in column_names:
await self.aalter_db_add_column('media')
# Check for other missing columns and add them if necessary
for column in ['links', 'metadata', 'screenshot']:
if column not in column_names:
await self.aalter_db_add_column(column)
async def aalter_db_add_column(self, new_column: str):
try:
async with aiosqlite.connect(self.db_path) as db:
await db.execute(f'ALTER TABLE crawled_data ADD COLUMN {new_column} TEXT DEFAULT ""')
await db.commit()
print(f"Added column '{new_column}' to the database.")
except Exception as e:
print(f"Error altering database to add screenshot column: {e}")
print(f"Error altering database to add {new_column} column: {e}")
async def aget_cached_url(self, url: str) -> Optional[Tuple[str, str, str, str, str, str, str, bool, str]]:
try:

View File

@@ -23,17 +23,18 @@ class AsyncWebCrawler:
self,
crawler_strategy: Optional[AsyncCrawlerStrategy] = None,
always_by_pass_cache: bool = False,
verbose: bool = False,
base_directory: str = str(Path.home()),
**kwargs,
):
self.crawler_strategy = crawler_strategy or AsyncPlaywrightCrawlerStrategy(
verbose=verbose
**kwargs
)
self.always_by_pass_cache = always_by_pass_cache
self.crawl4ai_folder = os.path.join(Path.home(), ".crawl4ai")
self.crawl4ai_folder = os.path.join(base_directory, ".crawl4ai")
os.makedirs(self.crawl4ai_folder, exist_ok=True)
os.makedirs(f"{self.crawl4ai_folder}/cache", exist_ok=True)
self.ready = False
self.verbose = verbose
self.verbose = kwargs.get("verbose", False)
async def __aenter__(self):
await self.crawler_strategy.__aenter__()
@@ -102,15 +103,14 @@ class AsyncWebCrawler:
t1 = time.time()
if user_agent:
self.crawler_strategy.update_user_agent(user_agent)
async_response : AsyncCrawlResponse = await self.crawler_strategy.crawl(url, **kwargs)
async_response: AsyncCrawlResponse = await self.crawler_strategy.crawl(url, screenshot=screenshot, **kwargs)
html = sanitize_input_encode(async_response.html)
screenshot_data = async_response.screenshot
t2 = time.time()
if verbose:
print(
f"[LOG] 🚀 Crawling done for {url}, success: {bool(html)}, time taken: {t2 - t1:.2f} seconds"
)
if screenshot:
screenshot_data = await self.crawler_strategy.take_screenshot(url)
crawl_result = await self.aprocess_html(
url,
@@ -127,7 +127,7 @@ class AsyncWebCrawler:
**kwargs,
)
crawl_result.status_code = async_response.status_code if async_response else 200
crawl_result.responser_headers = async_response.response_headers if async_response else {}
crawl_result.response_headers = async_response.response_headers if async_response else {}
crawl_result.success = bool(html)
crawl_result.session_id = kwargs.get("session_id", None)
return crawl_result
@@ -203,11 +203,11 @@ class AsyncWebCrawler:
)
if result is None:
raise ValueError(f"Failed to extract content from the website: {url}")
raise ValueError(f"Process HTML, Failed to extract content from the website: {url}")
except InvalidCSSSelectorError as e:
raise ValueError(str(e))
except Exception as e:
raise ValueError(f"Failed to extract content from the website: {url}, error: {str(e)}")
raise ValueError(f"Process HTML, Failed to extract content from the website: {url}, error: {str(e)}")
cleaned_html = sanitize_input_encode(result.get("cleaned_html", ""))
markdown = sanitize_input_encode(result.get("markdown", ""))

View File

@@ -16,8 +16,6 @@ from .utils import (
CustomHTML2Text
)
class ContentScrappingStrategy(ABC):
@abstractmethod
def scrap(self, url: str, html: str, **kwargs) -> Dict[str, Any]:
@@ -129,7 +127,7 @@ class WebScrappingStrategy(ContentScrappingStrategy):
image_size = 0 #int(fetch_image_file_size(img,base_url) or 0)
image_format = os.path.splitext(img.get('src',''))[1].lower()
# Remove . from format
image_format = image_format.strip('.')
image_format = image_format.strip('.').split('?')[0]
score = 0
if height_value:
if height_unit == 'px' and height_value > 150:
@@ -158,6 +156,7 @@ class WebScrappingStrategy(ContentScrappingStrategy):
return None
return {
'src': img.get('src', ''),
'data-src': img.get('data-src', ''),
'alt': img.get('alt', ''),
'desc': find_closest_parent_with_useful_text(img),
'score': score,
@@ -171,9 +170,11 @@ class WebScrappingStrategy(ContentScrappingStrategy):
element.extract()
return False
# if element.name == 'img':
# process_image(element, url, 0, 1)
# return True
if element.name in ['script', 'style', 'link', 'meta', 'noscript']:
if element.name == 'img':
process_image(element, url, 0, 1)
element.decompose()
return False
@@ -273,11 +274,14 @@ class WebScrappingStrategy(ContentScrappingStrategy):
# Replace base64 data with empty string
img['src'] = base64_pattern.sub('', src)
cleaned_html = str(body).replace('\n\n', '\n').replace(' ', ' ')
cleaned_html = sanitize_html(cleaned_html)
h = CustomHTML2Text()
h.ignore_links = True
h.body_width = 0
try:
markdown = h.handle(cleaned_html)
except Exception as e:
markdown = h.handle(sanitize_html(cleaned_html))
markdown = markdown.replace(' ```', '```')
try:
@@ -286,6 +290,7 @@ class WebScrappingStrategy(ContentScrappingStrategy):
print('Error extracting metadata:', str(e))
meta = {}
cleaned_html = sanitize_html(cleaned_html)
return {
'markdown': markdown,
'cleaned_html': cleaned_html,

View File

@@ -80,6 +80,7 @@ class LLMExtractionStrategy(ExtractionStrategy):
self.word_token_rate = kwargs.get("word_token_rate", WORD_TOKEN_RATE)
self.apply_chunking = kwargs.get("apply_chunking", True)
self.base_url = kwargs.get("base_url", None)
self.extra_args = kwargs.get("extra_args", {})
if not self.apply_chunking:
self.chunk_token_threshold = 1e9
@@ -111,7 +112,13 @@ class LLMExtractionStrategy(ExtractionStrategy):
"{" + variable + "}", variable_values[variable]
)
response = perform_completion_with_backoff(self.provider, prompt_with_variables, self.api_token, base_url=self.base_url) # , json_response=self.extract_type == "schema")
response = perform_completion_with_backoff(
self.provider,
prompt_with_variables,
self.api_token,
base_url=self.base_url,
extra_args = self.extra_args
) # , json_response=self.extract_type == "schema")
try:
blocks = extract_xml_data(["blocks"], response.choices[0].message.content)['blocks']
blocks = json.loads(blocks)

View File

@@ -18,5 +18,5 @@ class CrawlResult(BaseModel):
metadata: Optional[dict] = None
error_message: Optional[str] = None
session_id: Optional[str] = None
responser_headers: Optional[dict] = None
response_headers: Optional[dict] = None
status_code: Optional[int] = None

View File

@@ -1,4 +1,4 @@
PROMPT_EXTRACT_BLOCKS = """YHere is the URL of the webpage:
PROMPT_EXTRACT_BLOCKS = """Here is the URL of the webpage:
<url>{URL}</url>
And here is the cleaned HTML content of that webpage:
@@ -79,7 +79,7 @@ To generate the JSON objects:
2. For each block:
a. Assign it an index based on its order in the content.
b. Analyze the content and generate ONE semantic tag that describe what the block is about.
c. Extract the text content, EXACTLY SAME AS GIVE DATA, clean it up if needed, and store it as a list of strings in the "content" field.
c. Extract the text content, EXACTLY SAME AS THE GIVE DATA, clean it up if needed, and store it as a list of strings in the "content" field.
3. Ensure that the order of the JSON objects matches the order of the blocks as they appear in the original HTML content.

View File

@@ -6,6 +6,7 @@ import json
import html
import re
import os
import platform
from html2text import HTML2Text
from .prompts import PROMPT_EXTRACT_BLOCKS
from .config import *
@@ -18,6 +19,46 @@ from requests.exceptions import InvalidSchema
class InvalidCSSSelectorError(Exception):
pass
def calculate_semaphore_count():
cpu_count = os.cpu_count()
memory_gb = get_system_memory() / (1024 ** 3) # Convert to GB
base_count = max(1, cpu_count // 2)
memory_based_cap = int(memory_gb / 2) # Assume 2GB per instance
return min(base_count, memory_based_cap)
def get_system_memory():
system = platform.system()
if system == "Linux":
with open('/proc/meminfo', 'r') as mem:
for line in mem:
if line.startswith('MemTotal:'):
return int(line.split()[1]) * 1024 # Convert KB to bytes
elif system == "Darwin": # macOS
import subprocess
output = subprocess.check_output(['sysctl', '-n', 'hw.memsize']).decode('utf-8')
return int(output.strip())
elif system == "Windows":
import ctypes
kernel32 = ctypes.windll.kernel32
c_ulonglong = ctypes.c_ulonglong
class MEMORYSTATUSEX(ctypes.Structure):
_fields_ = [
('dwLength', ctypes.c_ulong),
('dwMemoryLoad', ctypes.c_ulong),
('ullTotalPhys', c_ulonglong),
('ullAvailPhys', c_ulonglong),
('ullTotalPageFile', c_ulonglong),
('ullAvailPageFile', c_ulonglong),
('ullTotalVirtual', c_ulonglong),
('ullAvailVirtual', c_ulonglong),
('ullAvailExtendedVirtual', c_ulonglong),
]
memoryStatus = MEMORYSTATUSEX()
memoryStatus.dwLength = ctypes.sizeof(MEMORYSTATUSEX)
kernel32.GlobalMemoryStatusEx(ctypes.byref(memoryStatus))
return memoryStatus.ullTotalPhys
else:
raise OSError("Unsupported operating system")
def get_home_folder():
home_folder = os.path.join(Path.home(), ".crawl4ai")
@@ -90,7 +131,7 @@ def split_and_parse_json_objects(json_string):
return parsed_objects, unparsed_segments
def sanitize_html(html):
# Replace all weird and special characters with an empty string
# Replace all unwanted and special characters with an empty string
sanitized_html = html
# sanitized_html = re.sub(r'[^\w\s.,;:!?=\[\]{}()<>\/\\\-"]', '', html)
@@ -260,7 +301,7 @@ def get_content_of_website(url, html, word_count_threshold = MIN_WORD_THRESHOLD,
if tag.name != 'img':
tag.attrs = {}
# Extract all img tgas inti [{src: '', alt: ''}]
# Extract all img tgas int0 [{src: '', alt: ''}]
media = {
'images': [],
'videos': [],
@@ -298,7 +339,7 @@ def get_content_of_website(url, html, word_count_threshold = MIN_WORD_THRESHOLD,
img.decompose()
# Create a function that replace content of all"pre" tage with its inner text
# Create a function that replace content of all"pre" tag with its inner text
def replace_pre_tags_with_text(node):
for child in node.find_all('pre'):
# set child inner html to its text
@@ -461,7 +502,7 @@ def get_content_of_website_optimized(url: str, html: str, word_count_threshold:
current_tag = tag
while current_tag:
current_tag = current_tag.parent
# Get the text content of the parent tag
# Get the text content from the parent tag
if current_tag:
text_content = current_tag.get_text(separator=' ',strip=True)
# Check if the text content has at least word_count_threshold
@@ -546,7 +587,7 @@ def get_content_of_website_optimized(url: str, html: str, word_count_threshold:
if score <= IMAGE_SCORE_THRESHOLD:
return None
return {
'src': img.get('src', ''),
'src': img.get('src', '').replace('\\"', '"').strip(),
'alt': img.get('alt', ''),
'desc': find_closest_parent_with_useful_text(img),
'score': score,
@@ -734,7 +775,14 @@ def extract_xml_data(tags, string):
return data
# Function to perform the completion with exponential backoff
def perform_completion_with_backoff(provider, prompt_with_variables, api_token, json_response = False, base_url=None):
def perform_completion_with_backoff(
provider,
prompt_with_variables,
api_token,
json_response = False,
base_url=None,
**kwargs
):
from litellm import completion
from litellm.exceptions import RateLimitError
max_attempts = 3
@@ -744,6 +792,9 @@ def perform_completion_with_backoff(provider, prompt_with_variables, api_token,
if json_response:
extra_args["response_format"] = { "type": "json_object" }
if kwargs.get("extra_args"):
extra_args.update(kwargs["extra_args"])
for attempt in range(max_attempts):
try:
response =completion(

View File

@@ -12,6 +12,7 @@ from typing import List
from concurrent.futures import ThreadPoolExecutor
from .config import *
import warnings
import json
warnings.filterwarnings("ignore", message='Field "model_name" has conflict with protected namespace "model_".')

View File

@@ -0,0 +1,48 @@
# File: async_webcrawler_multiple_urls_example.py
import os, sys
# append 2 parent directories to sys.path to import crawl4ai
parent_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(parent_dir)
import asyncio
from crawl4ai import AsyncWebCrawler
async def main():
# Initialize the AsyncWebCrawler
async with AsyncWebCrawler(verbose=True) as crawler:
# List of URLs to crawl
urls = [
"https://example.com",
"https://python.org",
"https://github.com",
"https://stackoverflow.com",
"https://news.ycombinator.com"
]
# Set up crawling parameters
word_count_threshold = 100
# Run the crawling process for multiple URLs
results = await crawler.arun_many(
urls=urls,
word_count_threshold=word_count_threshold,
bypass_cache=True,
verbose=True
)
# Process the results
for result in results:
if result.success:
print(f"Successfully crawled: {result.url}")
print(f"Title: {result.metadata.get('title', 'N/A')}")
print(f"Word count: {len(result.markdown.split())}")
print(f"Number of links: {len(result.links.get('internal', [])) + len(result.links.get('external', []))}")
print(f"Number of images: {len(result.media.get('images', []))}")
print("---")
else:
print(f"Failed to crawl: {result.url}")
print(f"Error: {result.error_message}")
print("---")
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,45 @@
import asyncio
from crawl4ai import AsyncWebCrawler, AsyncPlaywrightCrawlerStrategy
async def main():
# Example 1: Setting language when creating the crawler
crawler1 = AsyncWebCrawler(
crawler_strategy=AsyncPlaywrightCrawlerStrategy(
headers={"Accept-Language": "fr-FR,fr;q=0.9,en-US;q=0.8,en;q=0.7"}
)
)
result1 = await crawler1.arun("https://www.example.com")
print("Example 1 result:", result1.extracted_content[:100]) # Print first 100 characters
# Example 2: Setting language before crawling
crawler2 = AsyncWebCrawler()
crawler2.crawler_strategy.headers["Accept-Language"] = "es-ES,es;q=0.9,en-US;q=0.8,en;q=0.7"
result2 = await crawler2.arun("https://www.example.com")
print("Example 2 result:", result2.extracted_content[:100])
# Example 3: Setting language when calling arun method
crawler3 = AsyncWebCrawler()
result3 = await crawler3.arun(
"https://www.example.com",
headers={"Accept-Language": "de-DE,de;q=0.9,en-US;q=0.8,en;q=0.7"}
)
print("Example 3 result:", result3.extracted_content[:100])
# Example 4: Crawling multiple pages with different languages
urls = [
("https://www.example.com", "fr-FR,fr;q=0.9"),
("https://www.example.org", "es-ES,es;q=0.9"),
("https://www.example.net", "de-DE,de;q=0.9"),
]
crawler4 = AsyncWebCrawler()
results = await asyncio.gather(*[
crawler4.arun(url, headers={"Accept-Language": lang})
for url, lang in urls
])
for url, result in zip([u for u, _ in urls], results):
print(f"Result for {url}:", result.extracted_content[:100])
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -10,6 +10,7 @@ import time
import json
import os
import re
from typing import Dict
from bs4 import BeautifulSoup
from pydantic import BaseModel, Field
from crawl4ai import AsyncWebCrawler
@@ -18,6 +19,8 @@ from crawl4ai.extraction_strategy import (
LLMExtractionStrategy,
)
__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))
print("Crawl4AI: Advanced Web Crawling and Data Extraction")
print("GitHub Repository: https://github.com/unclecode/crawl4ai")
print("Twitter: @unclecode")
@@ -30,7 +33,7 @@ async def simple_crawl():
result = await crawler.arun(url="https://www.nbcnews.com/business")
print(result.markdown[:500]) # Print first 500 characters
async def js_and_css():
async def simple_example_with_running_js_code():
print("\n--- Executing JavaScript and Using CSS Selectors ---")
# New code to handle the wait_for parameter
wait_for = """() => {
@@ -47,12 +50,21 @@ async def js_and_css():
result = await crawler.arun(
url="https://www.nbcnews.com/business",
js_code=js_code,
# css_selector="article.tease-card",
# wait_for=wait_for,
bypass_cache=True,
)
print(result.markdown[:500]) # Print first 500 characters
async def simple_example_with_css_selector():
print("\n--- Using CSS Selectors ---")
async with AsyncWebCrawler(verbose=True) as crawler:
result = await crawler.arun(
url="https://www.nbcnews.com/business",
css_selector=".wide-tease-item__description",
bypass_cache=True,
)
print(result.markdown[:500]) # Print first 500 characters
async def use_proxy():
print("\n--- Using a Proxy ---")
print(
@@ -66,6 +78,28 @@ async def use_proxy():
# )
# print(result.markdown[:500]) # Print first 500 characters
async def capture_and_save_screenshot(url: str, output_path: str):
async with AsyncWebCrawler(verbose=True) as crawler:
result = await crawler.arun(
url=url,
screenshot=True,
bypass_cache=True
)
if result.success and result.screenshot:
import base64
# Decode the base64 screenshot data
screenshot_data = base64.b64decode(result.screenshot)
# Save the screenshot as a JPEG file
with open(output_path, 'wb') as f:
f.write(screenshot_data)
print(f"Screenshot saved successfully to {output_path}")
else:
print("Failed to capture screenshot")
class OpenAIModelFee(BaseModel):
model_name: str = Field(..., description="Name of the OpenAI model.")
input_fee: str = Field(..., description="Fee for input token for the OpenAI model.")
@@ -73,27 +107,30 @@ class OpenAIModelFee(BaseModel):
..., description="Fee for output token for the OpenAI model."
)
async def extract_structured_data_using_llm():
print("\n--- Extracting Structured Data with OpenAI ---")
print(
"Note: Set your OpenAI API key as an environment variable to run this example."
)
if not os.getenv("OPENAI_API_KEY"):
print("OpenAI API key not found. Skipping this example.")
async def extract_structured_data_using_llm(provider: str, api_token: str = None, extra_headers: Dict[str, str] = None):
print(f"\n--- Extracting Structured Data with {provider} ---")
if api_token is None and provider != "ollama":
print(f"API token is required for {provider}. Skipping this example.")
return
extra_args = {}
if extra_headers:
extra_args["extra_headers"] = extra_headers
async with AsyncWebCrawler(verbose=True) as crawler:
result = await crawler.arun(
url="https://openai.com/api/pricing/",
word_count_threshold=1,
extraction_strategy=LLMExtractionStrategy(
provider="openai/gpt-4o",
api_token=os.getenv("OPENAI_API_KEY"),
provider=provider,
api_token=api_token,
schema=OpenAIModelFee.schema(),
extraction_type="schema",
instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens.
Do not miss any models in the entire content. One extracted model JSON format should look like this:
{"model_name": "GPT-4", "input_fee": "US$10.00 / 1M tokens", "output_fee": "US$30.00 / 1M tokens"}.""",
extra_args=extra_args
),
bypass_cache=True,
)
@@ -320,6 +357,28 @@ async def crawl_dynamic_content_pages_method_3():
await crawler.crawler_strategy.kill_session(session_id)
print(f"Successfully crawled {len(all_commits)} commits across 3 pages")
async def crawl_custom_browser_type():
# Use Firefox
start = time.time()
async with AsyncWebCrawler(browser_type="firefox", verbose=True, headless = True) as crawler:
result = await crawler.arun(url="https://www.example.com", bypass_cache=True)
print(result.markdown[:500])
print("Time taken: ", time.time() - start)
# Use WebKit
start = time.time()
async with AsyncWebCrawler(browser_type="webkit", verbose=True, headless = True) as crawler:
result = await crawler.arun(url="https://www.example.com", bypass_cache=True)
print(result.markdown[:500])
print("Time taken: ", time.time() - start)
# Use Chromium (default)
start = time.time()
async with AsyncWebCrawler(verbose=True, headless = True) as crawler:
result = await crawler.arun(url="https://www.example.com", bypass_cache=True)
print(result.markdown[:500])
print("Time taken: ", time.time() - start)
async def speed_comparison():
# print("\n--- Speed Comparison ---")
# print("Firecrawl (simulated):")
@@ -387,13 +446,31 @@ async def speed_comparison():
async def main():
await simple_crawl()
await js_and_css()
await simple_example_with_running_js_code()
await simple_example_with_css_selector()
await use_proxy()
await capture_and_save_screenshot("https://www.example.com", os.path.join(__location__, "tmp/example_screenshot.jpg"))
await extract_structured_data_using_css_extractor()
# LLM extraction examples
await extract_structured_data_using_llm()
await extract_structured_data_using_llm("huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct", os.getenv("HUGGINGFACE_API_KEY"))
await extract_structured_data_using_llm("openai/gpt-4", os.getenv("OPENAI_API_KEY"))
await extract_structured_data_using_llm("ollama/llama3.2")
# You always can pass custom headers to the extraction strategy
custom_headers = {
"Authorization": "Bearer your-custom-token",
"X-Custom-Header": "Some-Value"
}
await extract_structured_data_using_llm(extra_headers=custom_headers)
# await crawl_dynamic_content_pages_method_1()
# await crawl_dynamic_content_pages_method_2()
await crawl_dynamic_content_pages_method_3()
await crawl_custom_browser_type()
await speed_comparison()

View File

@@ -6,7 +6,5 @@ numpy>=1.26.0,<2.1.1
pillow==10.4.0
playwright==1.47.0
python-dotenv==1.0.1
requests==2.32.3
PyYAML==6.0.2
requests>=2.26.0,<2.32.3
beautifulsoup4==4.12.3
psutil==6.0.0

View File

@@ -4,6 +4,7 @@ import os
from pathlib import Path
import shutil
import subprocess
import sys
# Create the .crawl4ai folder in the user's home directory if it doesn't exist
# If the folder already exists, remove the cache folder
@@ -35,20 +36,22 @@ transformer_requirements = ["transformers", "tokenizers", "onnxruntime"]
cosine_similarity_requirements = ["torch", "transformers", "nltk", "spacy"]
sync_requirements = ["selenium"]
def post_install():
print("Running post-installation setup...")
def install_playwright():
print("Installing Playwright browsers...")
try:
subprocess.check_call(["playwright", "install"])
subprocess.check_call([sys.executable, "-m", "playwright", "install"])
print("Playwright installation completed successfully.")
except subprocess.CalledProcessError:
print("Error during Playwright installation. Please run 'playwright install' manually.")
except FileNotFoundError:
print("Playwright not found. Please ensure it's installed and run 'playwright install' manually.")
except subprocess.CalledProcessError as e:
print(f"Error during Playwright installation: {e}")
print("Please run 'python -m playwright install' manually after the installation.")
except Exception as e:
print(f"Unexpected error during Playwright installation: {e}")
print("Please run 'python -m playwright install' manually after the installation.")
class PostInstallCommand(install):
def run(self):
install.run(self)
post_install()
install_playwright()
setup(
name="Crawl4AI",
@@ -61,7 +64,7 @@ setup(
author_email="unclecode@kidocode.com",
license="MIT",
packages=find_packages(),
install_requires=default_requirements,
install_requires=default_requirements + ["playwright"], # Add playwright to default requirements
extras_require={
"torch": torch_requirements,
"transformer": transformer_requirements,

View File

@@ -5,7 +5,7 @@ import asyncio
import time
# Add the parent directory to the Python path
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
parent_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(parent_dir)
from crawl4ai.async_webcrawler import AsyncWebCrawler

View File

@@ -0,0 +1,124 @@
import os
import sys
import pytest
import asyncio
import base64
from PIL import Image
import io
# Add the parent directory to the Python path
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(parent_dir)
from crawl4ai.async_webcrawler import AsyncWebCrawler
@pytest.mark.asyncio
async def test_basic_screenshot():
async with AsyncWebCrawler(verbose=True) as crawler:
url = "https://example.com" # A static website
result = await crawler.arun(url=url, bypass_cache=True, screenshot=True)
assert result.success
assert result.screenshot is not None
# Verify the screenshot is a valid image
image_data = base64.b64decode(result.screenshot)
image = Image.open(io.BytesIO(image_data))
assert image.format == "PNG"
@pytest.mark.asyncio
async def test_screenshot_with_wait_for():
async with AsyncWebCrawler(verbose=True) as crawler:
# Using a website with dynamic content
url = "https://www.youtube.com"
wait_for = "css:#content" # Wait for the main content to load
result = await crawler.arun(
url=url,
bypass_cache=True,
screenshot=True,
wait_for=wait_for
)
assert result.success
assert result.screenshot is not None
# Verify the screenshot is a valid image
image_data = base64.b64decode(result.screenshot)
image = Image.open(io.BytesIO(image_data))
assert image.format == "PNG"
# You might want to add more specific checks here, like image dimensions
# or even use image recognition to verify certain elements are present
@pytest.mark.asyncio
async def test_screenshot_with_js_wait_for():
async with AsyncWebCrawler(verbose=True) as crawler:
url = "https://www.amazon.com"
wait_for = "js:() => document.querySelector('#nav-logo-sprites') !== null"
result = await crawler.arun(
url=url,
bypass_cache=True,
screenshot=True,
wait_for=wait_for
)
assert result.success
assert result.screenshot is not None
image_data = base64.b64decode(result.screenshot)
image = Image.open(io.BytesIO(image_data))
assert image.format == "PNG"
@pytest.mark.asyncio
async def test_screenshot_without_wait_for():
async with AsyncWebCrawler(verbose=True) as crawler:
url = "https://www.nytimes.com" # A website with lots of dynamic content
result = await crawler.arun(url=url, bypass_cache=True, screenshot=True)
assert result.success
assert result.screenshot is not None
image_data = base64.b64decode(result.screenshot)
image = Image.open(io.BytesIO(image_data))
assert image.format == "PNG"
@pytest.mark.asyncio
async def test_screenshot_comparison():
async with AsyncWebCrawler(verbose=True) as crawler:
url = "https://www.reddit.com"
wait_for = "css:#SHORTCUT_FOCUSABLE_DIV"
# Take screenshot without wait_for
result_without_wait = await crawler.arun(
url=url,
bypass_cache=True,
screenshot=True
)
# Take screenshot with wait_for
result_with_wait = await crawler.arun(
url=url,
bypass_cache=True,
screenshot=True,
wait_for=wait_for
)
assert result_without_wait.success and result_with_wait.success
assert result_without_wait.screenshot is not None
assert result_with_wait.screenshot is not None
# Compare the two screenshots
image_without_wait = Image.open(io.BytesIO(base64.b64decode(result_without_wait.screenshot)))
image_with_wait = Image.open(io.BytesIO(base64.b64decode(result_with_wait.screenshot)))
# This is a simple size comparison. In a real-world scenario, you might want to use
# more sophisticated image comparison techniques.
assert image_with_wait.size[0] >= image_without_wait.size[0]
assert image_with_wait.size[1] >= image_without_wait.size[1]
# Entry point for debugging
if __name__ == "__main__":
pytest.main([__file__, "-v"])